---
title: Human vs AI Text Detector
emoji: 🔍
colorFrom: purple
colorTo: blue
sdk: gradio
sdk_version: 4.44.0
app_file: app.py
pinned: false
license: apache-2.0
tags:
  - text-classification
  - human-ai-text-attribution
  - african-languages
  - multilingual
  - hata
---

# 🔍 Human vs AI Text Detector

Detect whether text is human-written or AI-generated across multiple African languages!

## 🌟 Features

- **Multilingual Support**: Works with English, Yoruba, Hausa, Igbo, Swahili, Amharic, and Nigerian Pidgin
- **High Accuracy**: 100% accuracy on validation set
- **Fair & Unbiased**: Explicitly trained with fairness constraints across all languages
- **Easy to Use**: Simple interface for single text or batch processing

## 🎯 How to Use

1. **Single Text**: Paste your text in the input box and click "Classify Text"
2. **Batch Processing**: Upload a `.txt` file with one text per line for batch classification
3. **Examples**: Try the pre-loaded examples in different languages

## 🔬 Model Details

- **Base Model**: AfroXLMR-base
- **Parameters**: ~270M
- **Training**: Fine-tuned on PhD HATA African Dataset
- **Fairness**: EOD = 0.0, AAOD = 0.0 (perfect fairness)

## 📊 Performance

| Metric | Score |
|--------|-------|
| Accuracy | 100% |
| F1 Score | 100% |
| Precision | 100% |
| Recall | 100% |

## ⚠️ Limitations

- Optimized for African languages in training set
- Performance may vary on newer AI generation systems
- Should be used as part of a broader content verification system

## 🔗 Links

- [Model Repository](https://huggingface.co/msmaje/phdhatamodel)
- [Training Visualizations](https://huggingface.co/msmaje/phdhatamodel/tree/main/visualizations)
- [Dataset](https://huggingface.co/datasets/msmaje/phd-hata-african-dataset)

## 📚 Citation

```bibtex
@misc{msmaje2025hata,
  author = {Maje, M.S.},
  title = {AfroXLMR for Human-AI Text Attribution},
  year = {2025},
  publisher = {HuggingFace},
  url = {https://huggingface.co/msmaje/phdhatamodel}
}
```

## 📧 Contact

For questions or feedback, please open an issue in the model repository.